nips nips2010 nips2010-114 nips2010-114-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Tim Rogers, Chuck Kalish, Joseph Harrison, Xiaojin Zhu, Bryan R. Gibson
Abstract: When the distribution of unlabeled data in feature space lies along a manifold, the information it provides may be used by a learner to assist classification in a semi-supervised setting. While manifold learning is well-known in machine learning, the use of manifolds in human learning is largely unstudied. We perform a set of experiments which test a human’s ability to use a manifold in a semisupervised learning task, under varying conditions. We show that humans may be encouraged into using the manifold, overcoming the strong preference for a simple, axis-parallel linear boundary. 1
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